Triple
T11633388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City Police Department 50th Precinct |
E276455
|
entity |
| Predicate | sectorOfOperation |
P100108
|
FINISHED |
| Object | northwest Bronx |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: northwest Bronx | Statement: [New York City Police Department 50th Precinct, sectorOfOperation, northwest Bronx]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorOfOperation Context triple: [New York City Police Department 50th Precinct, sectorOfOperation, northwest Bronx]
-
A.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
B.
sectorServed
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
sectorBase
Indicates that one entity serves as the primary base or foundational location for operations within a particular sector of another entity.
-
D.
sector
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
E.
sectorCode
Indicates the classification code that identifies the economic or organizational sector associated with an entity or activity.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25aa9188190ab13d79139f37e7e |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
| PDg | Predicate description generation | batch_69d87f30642c8190ad94fa061cde186b |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:39 p.m.